Structured Point Cloud Data Analysis Via Regularized Tensor Regression for Process Modeling and Optimization
From MaRDI portal
Publication:6621650
DOI10.1080/00401706.2018.1529628MaRDI QIDQ6621650
Massimo Pacella, Hao Yan, Kamran Paynabar
Publication date: 18 October 2024
Published in: Technometrics (Search for Journal in Brave)
Cites Work
- Tensor Decompositions and Applications
- Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer
- Principal component analysis.
- Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion
- Multiscale Adaptive Regression Models for Neuroimaging Data
- Three-dimensional alpha shapes
- Unified functional tolerancing approach for precision cylindrical components
- Tensor Regression with Applications in Neuroimaging Data Analysis
- Fast BivariateP-Splines: The Sandwich Smoother
- Fast function-on-scalar regression with penalized basis expansions
- Unnamed Item
- Unnamed Item
Related Items (7)
A Statistical Approach to Surface Metrology for 3D-Printed Stainless Steel ⋮ Analyzing Nonparametric Part-to-Part Variation in Surface Point Cloud Data ⋮ Image-Based Feedback Control Using Tensor Analysis ⋮ Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior ⋮ Tensor-Based Temporal Control for Partially Observed High-Dimensional Streaming Data ⋮ Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes With Heterogeneous Sources of Data ⋮ Federated Multiple Tensor-on-Tensor Regression (FedMTOT) for Multimodal Data Under Data-Sharing Constraints
This page was built for publication: Structured Point Cloud Data Analysis Via Regularized Tensor Regression for Process Modeling and Optimization